Abstract
Computational Thinking (CT) is pervasive in our daily lives and is useful for problem-solving. Decision-making is a crucial part of problem-solving. In the extant literature, problem-solving strategies in educational settings are often conveniently attributed to intuition; however, it is well documented that computer programmers might even have difficulty describing about their intuitive insights during problem-solving using natural language (such as English), and subsequently convert what has been described using words into software code. Hence, a more analytical approach using mathematical equations and descriptions of CT is offered in this paper as a potential form of rudimentary scaffolding, which might be useful to facilitators and learners of CT-related activities. In the present paper, the decision-making processes during an unplugged CT activity are delineated via Grey-based mathematical equations, which is useful for informing educators who may wish to explain to their learners about the various aspects of CT which are involved in the unplugged activity and simultaneously use these mathematical equations as scaffolds between the unplugged activity and computer code programming. This theoretical manuscript may serve as a base for learners, should the facilitator ask them to embark on a software programming activity that is closely associated to the unplugged CT activity.
Highlights
In computer programming education, there might be an overemphasis on students' acquisition of the syntax of a programming language; often at the expense of development of problem-solving skills (McGill & Volet, 1997). Somers (2017) notices that programmers do not work on a problem directly
Grey-based mathematical equations have been utilised in the present paper to depict what might be involved in decision making during an unplugged Computational Thinking (CT) activity
An analytical approach using mathematical equations and descriptions of CT has been offered in this paper as a potential form of rudimentary scaffolding, which might be useful to facilitators and learners of CTrelated activities
Summary
There might be an overemphasis on students' acquisition of the syntax of a programming language; often at the expense of development of problem-solving skills (McGill & Volet, 1997). Somers (2017) notices that programmers do not work on a problem directly. In the present paper, for the purpose of “operationalising” CT concepts for utilisation of mathematical equations in decision-making and problem-solving using a computer programming language, we follow the conceptual framework offered by Gouws et al (2013) who have more concisely elucidated CT concepts for the field of education The constituents of this mental model of CT offered by Gouws et al (2013) include decomposition, algorithmic thinking, abstraction of data and. The present paper purports to explore this “thinking” part of computational thinking via the decision-making portions of problem-solving; first from the perspective of a human learner playing with the programmable toy mouse in an unplugged computational thinking activity, and subsequently from the perspective of a computer programmer who is programming the software version of a self-navigating mouse that can autonomously reach its objectives. The direction of future research will be presented in the conclusion section
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